Y. Hayashi, A. Imura, and K. Yoshida, "Fuzzy neural expert system and its application to medical diagnosis," in Proc. 8th Int. Congr. Cybernetics and Systems, 1990, pp. 54--61. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Prototype Based Rules - a New Way to Understand the Data. - Duch, Grudzinski (2001) (Correct)
....of 82 and led to 4 prototype vectors only. The leave one out result with these 4 prototypes is 88.7 , or just one error more than in case of the best logical rules [2] This result was obtained without any feature selection and optimization of similarity function. Hepatobiliary disorders data [17] contain medical records of 536 patients obtained from a university affiliated Tokyobased hospital, with four types of hepatobiliary disorders. The records include results of 9 biochemical tests and sex of the patient. The same 163 cases as in [17] were used as the test data. For this dataset a ....
....similarity function. Hepatobiliary disorders data [17] contain medical records of 536 patients obtained from a university affiliated Tokyobased hospital, with four types of hepatobiliary disorders. The records include results of 9 biochemical tests and sex of the patient. The same 163 cases as in [17] were used as the test data. For this dataset a large number of crisp logic rules is generated [2] with 49 rules only about 63 accuracy on the test set was achieved. Although fuzzy rules based on Gaussian or triangular membership functions give higher accuracy (about 75 76 ) over 100 are ....
Hayashi Y, Imura A, Yoshida K. Fuzzy neural expert system and its application to medical diagnosis. In: 8th International Congress on Cybernetics and Systems, New York City 1990, pp. 54-61
A New Methodology of Extraction, Optimization and.. - Duch, Adamczak.. (2000) (1 citation) (Correct)
....50 fuzzy rules 73.8 our result CART, 11 nodes 73.7 Ref. 79] C4.5 73.0 Ref. 88] CART 72.8 Ref. 88] Kohonen SOM 72.2 Ref. 88] kNN 71.9 Ref. 88] Reclasssification C MLP2LN, 2 rules 77.7 our result C MLP2LN, 1 rule 75.0 our result I. Hepatobiliary disorders This data, used previously in [91], contains medical records of 536 patients admitted to a university affiliated Tokyo based hospital, with four types of hepatobiliary disorders: alcoholic liver damage, primary hepatoma, liver cirrhosis and cholelithiasis. The records included results of 9 biochemical tests and sex of the patient. ....
....of 536 patients admitted to a university affiliated Tokyo based hospital, with four types of hepatobiliary disorders: alcoholic liver damage, primary hepatoma, liver cirrhosis and cholelithiasis. The records included results of 9 biochemical tests and sex of the patient. The same 163 cases as in [91] were used as the test data. In the previous work three fuzzy sets per each input were assigned using recommendation of the medical experts. A fuzzy neural network was constructed and trained until 100 correct answers were obtained on the training set. The accuracy on the test set varied from ....
Y. Hayashi, A. Imura, K. Yoshida, "Fuzzy neural expert system and its application to medical diagnosis", in: 8th International Congress on Cybernetics and Systems, New York City 1990, pp. 54-61
A Neuro-Fuzzy Approach to Medical Diagnostics - Eklund, Fullér (1993) (1 citation) (Correct)
....Finland Robert Fuller Department of Computer Science, Eotvos Lorand University, P.O.Box 157, H 1502 Budapest 112, Hungary Abstract There has been growing interest and activity in the area of medical decision making, especially in the last 20 years. As it has been pointed out by many authors [Adl86, Hay90, San92, Wan91], fuzzy set theory and neural nets have a number of properties that make them suitable for formalizing the uncertain information upon which medical diagnosis and treatment is usually based. Generalizing the earlier results of the first author [Ekl92] we provide a formal model of this process ....
Y.Hayashi and A.Imura, Fuzzy neural expert system and its application to medical diagnosis, in: C.N. Manikopoulos, ed., Proceedings of the 8th International Congress of Cybernetics and Systems, New Jersey Institute of Technology Press, Newark, NJ, 1990 54-61.
Eliminators and Classifiers - Duch, Adamczak, Hayashi (2000) Self-citation (Hayashi) (Correct)
....to LDA hyperplane a soft logistic function is used, corresponding to a neural network with singe neuron. The weights and bias are fixed by the LDA solution, only the slope of the function is optimized. 4 Real life example Hepatobiliary disorders data, used previously in several studies [17, 11, 12, 16], contains medical records of 536 patients admitted to a university affiliated Tokyo based hospital, with four types of hepatobiliary disorders: alcoholic liver damage (AL) primary hepatoma (PH) liver cirrhosis (LC) and cholelithiasis (CH) The records includes results of 9 biochemical tests and ....
....to a university affiliated Tokyo based hospital, with four types of hepatobiliary disorders: alcoholic liver damage (AL) primary hepatoma (PH) liver cirrhosis (LC) and cholelithiasis (CH) The records includes results of 9 biochemical tests and sex of the patient. The same 163 cases as in [17] were used as the test data. In the previous work three fuzzy sets per each input were assigned using recommendation of the medical experts. A fuzzy neural network was constructed and trained until 100 correct answers were obtained on the training set. The accuracy on the test set varied from ....
Y. Hayashi, A. Imura, K. Yoshida, "Fuzzy neural expert system and its application to medical diagnosis", in: 8th International Congress on Cybernetics and Systems, New York City 1990, pp. 54-61
Computational Intelligence Methods for Rule-Based Data.. - Duch, Setiono, Zurada (2004) (Correct)
No context found.
Y. Hayashi, A. Imura, and K. Yoshida, "Fuzzy neural expert system and its application to medical diagnosis," in Proc. 8th Int. Congr. Cybernetics and Systems, 1990, pp. 54--61.
Meta-learning via Search Combined with Parameter Optimization - Duch, Grudzinski (2002) (Correct)
No context found.
Hayashi, Y. , Imura, A., and Yoshida, K. (1990): Fuzzy neural expert system and its application to medical diagnosis. In: 8th International Congress on Cybernetics and Systems, New York, pp. 54-61
Meta-Learning: Searching in the Model Space - Duch, Grudzinski (2001) (Correct)
No context found.
Y. Hayashi, A. Imura, K. Yoshida, Fuzzy neural expert system and its application to medical diagnosis. In: 8th International Congress on Cybernetics and Systems, New York City 1990, pp. 54-61
Computational Intelligence Methods for Rule-Based Data.. - Duch, Setiono, Zurada (2004) (Correct)
No context found.
Y. Hayashi, A. Imura, and K. Yoshida, "Fuzzy neural expert system and its application to medical diagnosis," in Proc. 8th Int. Congr. Cybernetics and Systems, 1990, pp. 54--61.
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